code: def __init__(self):
      super(Net, self).__init__()
      self.conv1 = nn.Sequential(
          nn.Conv2d(  # (1*28*28)
              in_channels=1,
              out_channels=16,
              kernel_size=5,
              stride=1,  # step length
              padding=2,
          ),  # (16*28*28)
          nn.ReLU(),
          nn.MaxPool2d(kernel_size=2),  # (16*14*14)
      )
      self.conv2 = nn.Sequential(  # 16*14*14
          nn.Conv2d(16, 32, 5, 1, 2),  # 32*14*14
          nn.ReLU(),
          nn.MaxPool2d(2),  # 32*7*7
      )
      # Add drop
      # self.conv2_drop = nn.Dropout2d()
      self.out = nn.Linear(32 * 7 * 7, 10)
  
file_path: AdvBox/DataPoison/poison_mnist_pytorch.py
imports: from __future__ import division
  from __future__ import print_function
  from builtins import range
  from past.utils import old_div
  import torch
  import torchvision
  import torch.nn
  import torch.nn.functional
  import torch.optim
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net()